Andrew Sunol
Bib: 13155 β’M β’Age: 32
New York, NY

Race Timeline and Course Information
Your journey through the course with elevation, pacing, and checkpoint details
β±οΈ Race Timeline
Watch your race unfold from start to finish
Splits & Pacing
Detailed breakdown of your race performance at each timing point
Checkpoint Splits
| Checkpoint | Distance | Time of Day | Time | Avg Pace | Segment Time | Segment Pace | Diff |
|---|---|---|---|---|---|---|---|
5K | 3.11 mi | 07:24:21 | 24:21 | 7:51 | 24:21 | 7:51 | - |
10K | 6.21 mi | 07:47:59 | 47:59 | 7:44 | 23:38 | 7:37 | -0:14 |
15K | 9.32 mi | 08:10:12 | 1:10:12 | 7:32 | 22:13 | 7:10 | -0:27 |
20K | 12.43 mi | 08:32:19 | 1:32:19 | 7:26 | 22:07 | 7:08 | -0:02 |
FINISH | 13.11 mi | 09:05:58 | 2:05:58 | 9:37 | 33:39 | 49:22 | +42:14 |
Checkpoint Splits Visualizations
Explore your race data through different visual perspectives. Scroll to discover each visualization.
πPace Line
Pace Progression
Track your pace changes throughout the race. Dot colors mark your quickest to easiest segments, relative to your own pace.
Fastest Pace
7:08 /mi
Average Pace
9:37 /mi
Slowest Pace
49:22 /mi
πSegments
Segment Time Comparison
Bar length shows time spent in each segment. Colors mark your faster to slower segments, relative to your own pace.
Time at Faster Pace
0:00
0% of race
Time at Steady Pace
1:32:19
73% of race
Time at Slower Pace
33:39
27% of race
Average Pace: 9:37 /mi
π¨Heatmap
Pace Heatmap
Where you sped up and eased off relative to your own pace across the race. Colors are relative to your own range, not to other runners.
Click or hover over segments to see details
β¨Sparklines
Checkpoint Splits with Pace Trends
Enhanced split table showing pace trends through mini sparkline visualizations.
Overall Pace Trend
| Checkpoint | Distance | Time of Day | Time | Avg Pace | Segment | Pace | Trend | Rank |
|---|---|---|---|---|---|---|---|---|
5K | 3.11 mi | 07:24:21 | 24:21 | 7:51 | 24:21 | 7:51 | #5467 | |
10K | 6.21 mi | 07:47:59 | 47:59 | 7:44 | 23:38 | 7:37 | #5013 | |
15K | 9.32 mi | 08:10:12 | 1:10:12 | 7:32 | 22:13 | 7:10 | #4246 | |
20K | 12.43 mi | 08:32:19 | 1:32:19 | 7:26 | 22:07 | 7:08 | #3743 | |
FINISH | 13.11 mi | 09:05:58 | 2:05:58 | 9:37 | 33:39 | 49:22 | #7059 |
Rankings
Your position at each checkpoint and how you ranked in each segment
Checkpoint and Segment Rankings
| Checkpoint | Distance | Seg. Dist | Overall | Males | M30-34 | Seg. Overall | Seg. Males | Seg. M30-34 |
|---|---|---|---|---|---|---|---|---|
| 5K | 3.11 mi | 3.11 mi | 5467 | 4156 | 944 | 2997(Top 10%) | 2416(Top 16%) | 564(Top 19%) |
| 10K | 6.21 mi | 3.10 mi | 5013+454 | 3832+324 | 878+66 | 4689(Top 16%) | 3601(Top 24%) | 825(Top 28%) |
| 15K | 9.32 mi | 3.11 mi | 4246+767 | 3298+534 | 763+115 | 2997(Top 10%) | 2416(Top 16%) | 564(Top 19%) |
| 20K | 12.43 mi | 3.11 mi | 3743+503 | 2949+349 | 690+73 | 2711(Top 9%) | 2201(Top 15%) | 528(Top 18%) |
| FINISH | 13.11 mi | 0.68 mi | 7059-3316 | 5163-2214 | 1099-409 | 9664(Top 32%) | 6667(Top 45%) | 1379(Top 47%) |
Segment Performance Analysis
10Kβ15K
0.0 - 3.1 mi
Overall
2997
Males
2416
M30-34
564
5Kβ10K
3.1 - 6.2 mi
Overall
4689
Males
3601
M30-34
825
10Kβ15K
6.2 - 9.3 mi
Overall
2997
Males
2416
M30-34
564
15Kβ20K
9.3 - 12.4 mi
Overall
2711
Males
2201
M30-34
528
20KβFINISH
12.4 - 13.1 mi
Overall
9664
Males
6667
M30-34
1379
Passing
Athletes you passed and who passed you throughout the race
Passing Analysis
| Segment | Athletes Passed | Passed By | Net Change | Start Rank | End Rank |
|---|---|---|---|---|---|
| Start β 5K | - | - | - | - | #5467 |
| 5K β 10K | 488* | 34 | +454 | #5467 | #5013 |
| 10K β 15K | 769* | 2 | +767 | #5013 | #4246 |
| 15K β 20K | 506* | 3 | +503 | #4246 | #3743 |
| 20K β FINISH | 68 | 200 | -3316 | #3743 | #7059 |
| TOTALS | 1831* | 239 | -1592 |
* Includes athletes who did not complete a segment (DNF/DNQ).
Passing Analysis Visualizations
Explore your passing analysis through 5 different visualizations. Scroll to discover each one.
πPosition Graph
π¨Heatmap Timeline
πPassing Circle
πPosition Flow
πRace Lanes
AI Key Insights
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Activity Data
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